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https://scholarbank.nus.edu.sg/handle/10635/17102
DC Field | Value | |
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dc.title | Health WARNer: An advance clinical decision support system, with knowledge discovery, integration and management features | |
dc.contributor.author | FARHAN GUL | |
dc.date.accessioned | 2010-05-13T19:32:28Z | |
dc.date.available | 2010-05-13T19:32:28Z | |
dc.date.issued | 2005-07-07 | |
dc.identifier.citation | FARHAN GUL (2005-07-07). Health WARNer: An advance clinical decision support system, with knowledge discovery, integration and management features. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/17102 | |
dc.description.abstract | This thesis describes HealthWARNer, which is based on Arden Syntax. HealthWARNer is an advance clinical decision support system, which is extremely flexible and has features to support knowledge discovery, integration and management. It is flexible enough to be integrated with any clinical application written in any language and running on any platform, making it extremely easy to adopt. It uses the clinical knowledge to generate alert for reducing clinical errors and constantly tries to evaluate, optimize existing treatment processes and discovers new knowledge. This is done through a process called the cycle of knowledge creation. HealthWARNer also removes the few remaining hurdles in Arden Syntax for a knowledge sharing so that it can be done without human intervention. We add the concept of central MLM processing engine which creates an option for multiple healthcare institutions to share knowledge and MLM processing engine. This gives them many benefits including disease-surveillance capability. | |
dc.language.iso | en | |
dc.subject | clinical decision support system knowledge discovery | |
dc.type | Thesis | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.contributor.supervisor | PUNG HUNG KENG | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF SCIENCE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Master's Theses (Open) |
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GulF.PDF | 1.23 MB | Adobe PDF | OPEN | None | View/Download |
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